Biology subjects

Graziani, M.

Publications and source records attributed to Graziani, M..

4 recordsLinked to original sources

bioRxiv2025

Long-term co-maturation of stem cell-derived microglia and neuronal networks: an optimized platform to assess human microglial contribution to neuronal function

Microglia-neuron interactions play a central role in a variety of central nervous system disorders. Technologies using human induced pluripotent stem cells (hiPSCs) have been developed to model human brain cells with the goal to understand their function. To effectively study neuro-immune crosstalk and investigate microglial contributions to neuronal network development and function, both microglia and neurons should co-mature allowing for long-term interactions throughout their differentiation. Here, we present a co-maturation protocol that robustly generates glutamatergic neuronal networks containing human iPSC-derived microglia. We validated the long-term co-cultures using single-cell transcriptomics, imaging and neuronal activity readouts. We show that astrocytes were required for long-term survival of microglia and for their integration into neuronal networks. Our co-maturation approach induced the typical ramified microglia morphology and characteristic microglia-neuron interactions. Homeostatic markers like P2RY12 and TMEM119 and neuronal remodeling associated genes were upregulated compared to microglia monocultures, highlighting the necessity of the environment to generate and maintain the context-dependent microglia signature in vitro. In this manuscript, we include the full optimization process of our co-maturation approach, a comprehensive description of the protocol, practical guidelines and troubleshooting tips. Our co-maturation model provides a powerful tool to assess the role of human microglia in modulating neuronal function and development in health and disease. HighlightsO_LIptimized human iPSC differentiation protocol that allows for co-maturation of microglia and Neurogenin2-induced neuronal networks. C_LIO_LIare required for long-term survival and integration of microglia into neuronal networks. C_LIO_LICo-maturation approach enables characteristic neuron-microglia interactions and induces signature morphology, transcriptome and proteins of human microglia. C_LI

neuroscience↗

bioRxiv2024

A microglia-containing cerebral organoid model to study early life immune challenges

Prenatal infections and activation of the maternal immune system have been proposed to contribute to causing neurodevelopmental disorders (NDDs), chronic conditions often linked to brain abnormalities. Microglia are the resident immune cells of the brain and play a key role in neurodevelopment. Disruption of microglial functions can lead to brain abnormalities and increase the risk of developing NDDs. How the maternal as well as the fetal immune system affect human neurodevelopment and contribute to NDDs remains unclear. An important reason for this knowledge gap is the fact that the impact of exposure to prenatal risk factors has been challenging to study in the human context. Here, we characterized a model of cerebral organoids (CO) with integrated microglia (COiMg). These organoids express typical microglial markers and respond to inflammatory stimuli. The presence of microglia influences cerebral organoid development, including cell density and neural differentiation, and regulates the expression of several ciliated mesenchymal cell markers. Moreover, COiMg and organoids without microglia show similar but also distinct responses to inflammatory stimuli. Additionally, IFN-{gamma} induced significant transcriptional and structural changes in the cerebral organoids, that appear to be regulated by the presence of microglia. Specifically, interferon-gamma (IFN-{gamma}) was found to alter the expression of genes linked to autism. This model provides a valuable tool to study how inflammatory perturbations and microglial presence affect neurodevelopmental processes.

neuroscience↗

bioRxiv2023

Signature Informed Sampling for Transcriptomic Data

With machine learning taking over biomedical applications, working with transcriptomic data on supervised learning tasks is challenging due to high dimensionality, low patient numbers and class imbalances. Machine learning models tend to overfit these data and do not generalise well on out-of-distribution samples. Data augmentation strategies help alleviate this by introducing synthetic data points and acting as regularisers. However, existing approaches are either computationally intensive, require population parametric estimates or generate insufficiently diverse samples. To address these challenges, we introduce two classes of phenotype driven data augmentation approaches - signature-dependent and signature-independent. The signature-dependent methods assume the existence of distinct gene signatures describing some phenotype and are simple, non-parametric, and novel data augmentation methods. The signature-independent methods are a modification of the established Gamma-Poisson and Poisson sampling methods for gene expression data. As case studies, we apply our augmentation methods to transcriptomic data of colorectal and breast cancer. Through discriminative and generative experiments with external validation, we show that our methods improve patient stratification by 5 - 15% over other augmentation methods in different cases. The study additionally provides insights into the limited benefits of over-augmenting data. The code is hosted on GitHub, and includes a link to the augmented datasets.

bioinformatics↗

bioRxiv2023

HIV-1 infection of genetically engineered iPSC-derived central nervous system-engrafted microglia in a humanized mouse model

The central nervous system (CNS) is a major human immunodeficiency virus type 1 reservoir. Microglia are the primary target cell of HIV-1 infection in the CNS. Current models have not allowed the precise molecular pathways of acute and chronic CNS microglial infection to be tested with in vivo genetic methods. Here, we describe a novel humanized mouse model utilizing human-induced pluripotent stem cell-derived microglia to xenograft into murine hosts. These mice are additionally engrafted with human peripheral blood mononuclear cells that served as a medium to establish a peripheral infection that then spread to the CNS microglia xenograft, modeling a trans-blood-brain barrier route of acute CNS HIV-1 infection with human target cells. The approach is compatible with iPSC genetic engineering, including inserting targeted transgenic reporter cassettes to track the xenografted human cells, enabling the testing of novel treatment and viral tracking strategies in a comparatively simple and cost-effective way vivo model for neuroHIV. ImportanceOur mouse model is a powerful tool for investigating the genetic mechanisms governing CNS HIV-1 infection and latency in the CNS at a single-cell level. A major advantage of our model is that it uses iPSC-derived microglia, which enables human genetics, including gene function and therapeutic gene manipulation, to be explored in vivo, which is more challenging to study with current hematopoietic stem cell-based models for neuroHIV. Our transgenic tracing of xenografted human cells will provide a quantitative medium to develop new molecular and epigenetic strategies for reducing the HIV-1 latent reservoir and to test the impact of therapeutic inflammation-targeting drug interventions on CNS HIV-1 latency.

neuroscience↗